IV, GMM or Likelihood Approach to Estimate Dynamic Panel Models When Either N or T or Both Are Large

31 Pages Posted: 31 Jan 2015

See all articles by Cheng Hsiao

Cheng Hsiao

University of Southern California - Department of Economics; National Taiwan University; National Bureau of Economic Research (NBER)

Junwei Zhang

University of Southern California

Date Written: January 28, 2015

Abstract

We examine the asymptotic properties of IV, GMM or MLE to estimate dynamic panel data models when either N or T or both are large. We show that the Anderson and Hsiao (1981, 1982) simple instrumental variable estimator (IV) or maximizing the likelihood function with initial value distribution properly treated (quasi-maximum likelihood estimator) is asymptotically unbiased when either N or T or both tend to infinity. On the other hand, the QMLE mistreating the initial value as fixed is asymptotically unbiased only if N is fixed and T is large. If both N and T are large and N/T → c (c ≠ 0, c < ∞) as T → ∞, it is asymptotically biased of order √(N/T). We also explore the source of the bias of the Arellano and Bond (1991) type GMM estimator. We show that it is asymptotically biased of order √(N/T) if T/N → c (c ≠ 0, c < ∞) as N → ∞ even if we restrict the number of instruments used. Monte Carlo studies show that whether an estimator is asymptotically biased or not has important implications on the actual size of the conventional t-test.

Keywords: IV, MLE, GMM, asymptotic bias, large N, T

JEL Classification: C12, C18, C23, C26

Suggested Citation

Hsiao, Cheng and Zhang, Junwei, IV, GMM or Likelihood Approach to Estimate Dynamic Panel Models When Either N or T or Both Are Large (January 28, 2015). USC-INET Research Paper No. 15-06, Available at SSRN: https://ssrn.com/abstract=2557676 or http://dx.doi.org/10.2139/ssrn.2557676

Cheng Hsiao (Contact Author)

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall, 300
Los Angeles, CA 90089
United States

National Taiwan University

1 Sec. 4, Roosevelt Road
Taipei, 106
Taiwan

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Junwei Zhang

University of Southern California ( email )

2250 Alcazar Street
Los Angeles, CA 90089
United States

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